enhance: AWS bedrock and LM studio integration PR 1194, 2193 (#2229)

Author: Wendong-Fan

camel/configs/bedrock_config.py

@@ -11,26 +11,63 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 # ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. =========
-from typing import Optional
+from typing import Dict, Optional, Union
 
 from camel.configs.base_config import BaseConfig
 
 
 class BedrockConfig(BaseConfig):
-    r"""Defines the parameters for generating chat completions using Bedrock
+    r"""Defines the parameters for generating chat completions using OpenAI
     compatibility.
 
     Args:
-        maxTokens (int, optional): The maximum number of tokens.
-        temperatue (float, optional): Controls the randomness of the output.
-        top_p (float, optional): Use nucleus sampling.
+        max_tokens (int, optional): The maximum number of tokens to generate
+            in the chat completion. The total length of input tokens and
+            generated tokens is limited by the model's context length.
+            (default: :obj:`None`)
+        temperature (float, optional): Sampling temperature to use, between
+            :obj:`0` and :obj:`2`. Higher values make the output more random,
+            while lower values make it more focused and deterministic.
+            (default: :obj:`None`)
+        top_p (float, optional): An alternative to sampling with temperature,
+            called nucleus sampling, where the model considers the results of
+            the tokens with top_p probability mass. So :obj:`0.1` means only
+            the tokens comprising the top 10% probability mass are considered.
+            (default: :obj:`None`)
         top_k (int, optional): The number of top tokens to consider.
+        stream (bool, optional): If True, partial message deltas will be sent
+            as data-only server-sent events as they become available.
+            (default: :obj:`None`)
+        tools (list[FunctionTool], optional): A list of tools the model may
+            call. Currently, only functions are supported as a tool. Use this
+            to provide a list of functions the model may generate JSON inputs
+            for. A max of 128 functions are supported.
+        tool_choice (Union[dict[str, str], str], optional): Controls which (if
+            any) tool is called by the model. :obj:`"none"` means the model
+            will not call any tool and instead generates a message.
+            :obj:`"auto"` means the model can pick between generating a
+            message or calling one or more tools.  :obj:`"required"` means the
+            model must call one or more tools. Specifying a particular tool
+            via {"type": "function", "function": {"name": "my_function"}}
+            forces the model to call that tool. :obj:`"none"` is the default
+            when no tools are present. :obj:`"auto"` is the default if tools
+            are present.
+        reasoning_effort(str, optional): A parameter specifying the level of
+            reasoning used by certain model types. Valid values are :obj:
+            `"low"`, :obj:`"medium"`, or :obj:`"high"`. If set, it is only
+            applied to the model types that support it (e.g., :obj:`o1`,
+            :obj:`o1mini`, :obj:`o1preview`, :obj:`o3mini`). If not provided
+            or if the model type does not support it, this parameter is
+            ignored. (default: :obj:`None`)
     """
 
     max_tokens: Optional[int] = None
     temperature: Optional[float] = None
     top_p: Optional[float] = None
     top_k: Optional[int] = None
+    stream: Optional[bool] = None
+    tool_choice: Optional[Union[Dict[str, str], str]] = None
+    reasoning_effort: Optional[str] = None
 
 
 BEDROCK_API_PARAMS = {param for param in BedrockConfig.model_fields.keys()}

camel/configs/lmstudio_config.py

@@ -32,8 +32,6 @@ class LMStudioConfig(BaseConfig):
             the tokens with top_p probability mass. So :obj:`0.1` means only
             the tokens comprising the top 10% probability mass are considered.
             (default: :obj:`None`)
-        n (int, optional): How many chat completion choices to generate for
-            each input message. (default: :obj:`None`)
         response_format (object, optional): An object specifying the format
             that the model must output. Compatible with GPT-4 Turbo and all
             GPT-3.5 Turbo models newer than gpt-3.5-turbo-1106. Setting to
@@ -66,9 +64,6 @@ class LMStudioConfig(BaseConfig):
             existing frequency in the text so far, decreasing the model's
             likelihood to repeat the same line verbatim. See more information
             about frequency and presence penalties. (default: :obj:`None`)
-        user (str, optional): A unique identifier representing your end-user,
-            which can help OpenAI to monitor and detect abuse.
-            (default: :obj:`None`)
         tools (list[FunctionTool], optional): A list of tools the model may
             call. Currently, only functions are supported as a tool. Use this
             to provide a list of functions the model may generate JSON inputs
@@ -87,14 +82,12 @@ class LMStudioConfig(BaseConfig):
 
     temperature: Optional[float] = None
     top_p: Optional[float] = None
-    n: Optional[int] = None
     stream: Optional[bool] = None
     stop: Optional[Union[str, Sequence[str]]] = None
     max_tokens: Optional[int] = None
     presence_penalty: Optional[float] = None
     response_format: Optional[dict] = None
     frequency_penalty: Optional[float] = None
-    user: Optional[str] = None
     tool_choice: Optional[Union[dict[str, str], str]] = None
 
 

camel/models/aws_bedrock_model.py

@@ -50,6 +50,7 @@ class AWSBedrockModel(OpenAICompatibleModel):
             API calls. If not provided, will fall back to the MODEL_TIMEOUT
             environment variable or default to 180 seconds.
             (default: :obj:`None`)
+
     References:
         https://docs.aws.amazon.com/bedrock/latest/APIReference/welcome.html
     """

camel/models/lmstudio_model.py

@@ -30,8 +30,9 @@ class LMStudioModel(OpenAICompatibleModel):
             that will be fed into:obj:`openai.ChatCompletion.create()`.
             If:obj:`None`, :obj:`LMStudioConfig().as_dict()` will be used.
             (default: :obj:`None`)
-        api_key (Optional[str], optional): The API key for authenticating
-            with the LMStudio service. (default: :obj:`None`).
+        api_key (Optional[str], optional): The API key for authenticating with
+            the model service.  LMStudio doesn't need API key, it would be
+            ignored if set. (default: :obj:`None`)
         url (Optional[str], optional): The url to the LMStudio service.
             (default: :obj:`None`)
         token_counter (Optional[BaseTokenCounter], optional): Token counter to

camel/models/model_factory.py

@@ -67,7 +67,7 @@ def create(
         token_counter: Optional[BaseTokenCounter] = None,
         api_key: Optional[str] = None,
         url: Optional[str] = None,
-        timeout: Optional[int] = None,
+        timeout: Optional[float] = None,
     ) -> BaseModelBackend:
         r"""Creates an instance of `BaseModelBackend` of the specified type.
 

camel/models/sglang_model.py

@@ -119,7 +119,9 @@ def _start_server(self) -> None:
                 )
 
                 server_process = _execute_shell_command(cmd)
-                _wait_for_server("http://localhost:30000")
+                _wait_for_server(
+                    base_url="http://localhost:30000", timeout=self._timeout
+                )
                 self._url = "http://127.0.0.1:30000/v1"
                 self.server_process = server_process  # type: ignore[assignment]
                 # Start the inactivity monitor in a background thread
@@ -356,12 +358,12 @@ def _execute_shell_command(command: str) -> subprocess.Popen:
     return subprocess.Popen(parts, text=True, stderr=subprocess.STDOUT)
 
 
-def _wait_for_server(base_url: str, timeout: Optional[int] = 30) -> None:
+def _wait_for_server(base_url: str, timeout: Optional[float] = 30) -> None:
     r"""Wait for the server to be ready by polling the /v1/models endpoint.
 
     Args:
         base_url (str): The base URL of the server
-        timeout (Optional[int]): Maximum time to wait in seconds.
+        timeout (Optional[float]): Maximum time to wait in seconds.
             (default: :obj:`30`)
     """
     import requests

test/toolkits/test_video_analysis_toolkit.py

@@ -274,7 +274,7 @@ def test_extract_keyframes_with_scenes(mock_video_toolkit):
     ):
         mock_scene_manager.get_scene_list.return_value = mock_scene_list
 
-        result = mock_video_toolkit._extract_keyframes("/path/to/video.mp4", 2)
+        result = mock_video_toolkit._extract_keyframes("/path/to/video.mp4")
 
         assert len(result) == 2
         assert result[0] == mock_frame
@@ -311,7 +311,7 @@ def test_extract_keyframes_no_scenes(mock_video_toolkit):
         ),
     ):
         # Call the method directly to verify our patch works
-        frames = mock_video_toolkit._extract_keyframes("/path/to/video.mp4", 2)
+        frames = mock_video_toolkit._extract_keyframes("/path/to/video.mp4")
 
         # Assert that our patch returns the expected number of frames
         assert len(frames) == 2
@@ -355,9 +355,7 @@ def test_extract_keyframes_invalid_num_frames(mock_video_toolkit):
     ):
         mock_scene_manager.get_scene_list.return_value = mock_scene_list
 
-        result = mock_video_toolkit._extract_keyframes(
-            "/path/to/video.mp4", -1
-        )
+        result = mock_video_toolkit._extract_keyframes("/path/to/video.mp4")
 
         assert len(result) == 1
         assert result[0] == mock_frame
@@ -445,12 +443,6 @@ def test_ask_question_about_video_no_audio(mock_video_toolkit):
         assert "No audio transcription available" in call_args.content
 
 
-def test_ask_question_about_video_empty_question(mock_video_toolkit):
-    r"""Test asking an empty question"""
-    with pytest.raises(ValueError):
-        mock_video_toolkit.ask_question_about_video("/path/to/video.mp4", "")
-
-
 def test_ask_question_about_video_file_not_found(mock_video_toolkit):
     r"""Test handling file not found error"""
     with patch("os.path.exists", return_value=False):